The skills gap behind agentic AI — and how Databricks is closing it with a new context engineer certification and agent trainings

As businesses strive to implement agentic AI, context engineering has emerged as a significant challenge, hindering the transition from pilot projects to tangible outcomes. Databricks has responded by introducing the Databricks Certified Context Engineer Associate beta exam, the first certification focused on the skills necessary for creating production-grade AI agent systems.

Context engineering involves curating and managing the right set of tokens, memory banks, and tool parameters to enable large language models (LLMs) to solve tasks effectively. Early participants in the certification have noted its depth and the importance of rigorous engineering over guesswork.

In addition, Databricks has expanded its learning catalog with courses tailored for the agentic era, reflecting a commitment to addressing context and reliability gaps. This shift in technical training is further supported by a free AI certification prep guide, acknowledging the growing use of AI tools like ChatGPT in exam preparation.

These efforts position Databricks as a leader in AI education and certification.